How do you optimize a large Cucumber regression suite for faster execution?

As a Cucumber suite grows into the hundreds or thousands of scenarios, runtime becomes dominated by a handful of specific factors, most of which have direct, well-established mitigations.

• Enable and tune parallel execution - configure the JUnit 5 Platform Suite's parallel execution properties and increase parallelism to match available CI resources, since sequential execution of a large suite scales linearly with scenario count.
• Ensure genuine per-scenario isolation - fix any shared mutable state (static fields, singletons) that would otherwise force serialization or cause intermittent failures once parallelism is increased.
• Use tag expressions to right-size CI runs - run a fast, targeted subset (like @smoke) on every commit, reserving the full suite for less frequent, scheduled runs.
• Minimize expensive setup in hooks - move genuinely one-time setup (like starting a shared test server) outside per-scenario @Before hooks where safe to do so, rather than repeating it for every scenario.
• Avoid unnecessary sleeps in step definitions - replace fixed waits with explicit, condition-based waits so tests only wait as long as actually needed.
• Profile slow scenarios specifically - a small number of disproportionately slow scenarios (often those hitting real external dependencies) frequently account for a large share of total suite runtime, and are worth optimizing or isolating individually rather than treating the whole suite as uniformly slow.

The highest-leverage change for most large suites is usually parallel execution combined with fixing whatever shared state prevents it from being enabled safely, since that directly attacks the dominant cost (sequential runtime scaling with scenario count) rather than shaving time off individual scenarios one at a time.